A Group Contribution Method for Predicting the Freezing Point of Ionic Liquids

Abstract

A simple group contribution method for the prediction of the freezing point for several ionic liquids is presented. Liquids have a characteristic temperature, known as their freezing point, at which they turn into solids. The melting point of a solid should theoretically be the same as the freezing point for the liquid. Greater differences between these quantities can be observed in ionic liquids. Some ionic liquids display substantial supercooling while being cooled at relatively high temperature. Experimental data from the freezing point (not melting point) for 40 ionic liquids were used to obtain the contributions for the cation-anion groups in a correlation set. The optimum parameters of the method were obtained using a genetic algorithm-based on multivariate linear regression. Then, the freezing points for another 23 ionic liquids were predicted, and the results were compared with experimental data available in the literature. The results show an average deviation of 5 %.